Molecular Alterations in Pediatric Fibroblastic/Myofibroblastic Tumors: An Appraisal of a Next Generation Sequencing Assay in a Retrospective Single Centre Study
Bibliographic record
Abstract
BACKGROUND: Pediatric fibroblastic/myofibroblastic tumors (PFMTs) can be challenging to definitively classify. Large case series or diagnostic updates have not been recently published despite identification of molecular alterations that could improve diagnostic accuracy. Our review of the literature found that over two-thirds of the more than 30 types of PFMTs harbor recurrent molecular alterations. We performed an institutional review of PFMTs to highlight limitations of a predominantly morphological classification, and evaluated the utility of a next-generation sequencing assay to aid diagnosis. METHODS: PFMTs identified over a period of 12 years were reviewed, categorized per the new WHO classification, and tested using the Oncomine Childhood Cancer Research Assay. RESULTS: Eighty-seven specimens from 58 patients were reviewed; 50 were chosen for molecular analysis, 16 (32%) lacking definitive classification. We identified alterations, some novel, in 33% of assayed cases. Expected alterations were identified for most known diagnoses and mutations were identified in 6 of 16 tumors (38%) that were initially unclassified. CONCLUSION: We confirmed a significant subset of PFMTs remain difficult to classify using current criteria, and that a combined DNA/RNA assay can identify alterations in many of these cases, improving diagnostic certainty and suggesting a clinical utility for challenging cases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".